Abstract

Foreign exchange trading has emerged in recent times as a significant activity in many countries. As with most forms of trading, the activity is influenced by many random parameters, so that the creation of a system that effectively emulates the trading process will be very helpful. This chapter presents a novel trading system using Machine Learning methods of Genetic Algorithms and Reinforcement Learning. The system emulates trader behavior on the Foreign Exchange market and finds the most profitable trading strategy.

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